Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks
IEEE Transactions on Computers
A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimisation: NSGA-II
PPSN VI Proceedings of the 6th International Conference on Parallel Problem Solving from Nature
New Metrics for Dominating Set Based Energy Efficient Activity Scheduling in Ad Hoc Networks
LCN '03 Proceedings of the 28th Annual IEEE International Conference on Local Computer Networks
Set k-cover algorithms for energy efficient monitoring in wireless sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
An Extended Localized Algorithm for Connected Dominating Set Formation in Ad Hoc Wireless Networks
IEEE Transactions on Parallel and Distributed Systems
On Constructing k-Connected k-Dominating Set in Wireless Networks
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
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Density control is a promising method to conserve system energy and prolonging lifetime of wireless sensor networks. In this paper, we address the issue of maintaining sensing coverage of surveillance target in large density wireless sensor networks and present an efficient technique for the selection of active sensor nodes. First, the At Most k-Coverage Problem (AM k-Coverage) is defined and modeled as a nonlinear integer programming. Second, Genetic Algorithm which is a quasi-parallel method to construct set cover is designed to solve the multi-objective nonlinear integer programming. And later by using Genetic Algorithm, a central algorithm is designed to organize a sensor network into coverage sets. Finally, Experimental results show that the proposed algorithm can construct the coverage sets reliably and reduce the number of active sensor nodes which is helpful to reduce system energy consumption and prolong the network lifespan.